With spending of big data technology nearing $57 billion last year, data science isn’t just for Google and Amazon anymore. In 2017, 53% of companies reported using big data analytics, up from only 17% just two years before.

And yet despite these attention-grabbing numbers, many non-tech companies are still wary of embracing big data, and with good reason. It can be intimidating, frustrating, and confusing to implement big data—but it doesn’t have to be.

With these compelling reasons and six simple steps, you can integrate data into your company’s processes and join the golden age of data science.

Why You Need Big Data

From branding your business to gaining valuable customer insight, there are many reasons why non-tech companies make the leap into the world of data. Here are some of the top ways to utilize data in your business.

  • Improve Customer Engagement: data can be used to recommend products or services based on past customer behavior, which can boost customer experience and ultimately loyalty.
  • Increase Profitability with Sales Prediction: companies can analyze sales data to predict sales trends. This knowledge can be projected onto production and operations to maximize profitability.
  • Cut Inventory Costs: going along with sales prediction, algorithms can be used to analyze past sales data along with other information that could affect sales so companies can stock shelves more efficiently. This type of data science can actually reduce inventory while increasing sales.

Integrate with Six Simple Steps

Firms that adopt a data-driven decision-making approach have a 6% higher output and productivity than would be expected, but how can you actually implement such data-driven decision-making in your business?

  1. Define Your Data Needs: be specific about the aim of data analysis in your company, what you hope to achieve and how it interacts with your broader business. Do you need to make better decisions about pricing? Do you want to predict sales trends? Do you want to improve marketing? Setting your intention is an important first step to incorporating big data in your company.
  2. Prioritize: once you understand what your company hopes to achieve with big data, prioritize your projects. It will be daunting, and impossible, to tackle them all at once. Identify which projects may have the highest impact and start with the first on that list.
  3. Use What You Have: before investing in a data management platform, identify and evaluate your current data sources and existing data warehouse that may already be in place at your company.
  4. Choose a Data Management Platform: take into account your return on investment, what kind of data you want to be collected and how, the architecture of your data analysis (who should see what), and the insights you want from the data when choosing your data management platform.
  5. Put Your Data Team at the Forefront: if you isolate your data team in IT or engineering, they will be too far from the business decisions they are meant to influence. A cross-functional team of data scientists and key decision makers will not have to waste time proving their usefulness but will be perfectly in line to make recommendations to stakeholders.
  6. Choose a High Visibility, High Impact Project: for your first foray into big data, choose a project that will have an immediate, positive impact on company efficiency or a visible increase in sales. This will help get all the members of your organization onboard and excited about your company’s venture into big data.

Big Data, Big Results

If your company has been considering adding big data into its daily operations, don’t delay any longer. When taken as a whole concept big data can certainly be daunting, but the above steps can help you seamlessly integrate big data in your business—and take your non-tech company to the next level in our technological age.

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